Ship drift

from datetime import datetime
from opendrift.models.shipdrift import ShipDrift

o = ShipDrift(loglevel=20)

o.add_readers_from_list([
    'https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml',
    'https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc',
    'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml'
    ])

15:23:10 INFO    opendrift:509: OpenDriftSimulation initialised (version 1.13.1 / v1.13.1-82-gbc545aa)

Seed ship elements at defined position and time Note: beam/length ratio is larger than allowed, but is then clipped internally

o.seed_elements(lon=5.0, lat=63.0, radius=1000, number=1000,
                time=datetime.utcnow(),
                length=80.0, beam=20.0, height=9.0, draft=4.0)

/root/project/examples/example_shipdrift.py:22: DeprecationWarning: datetime.datetime.utcnow() is deprecated and scheduled for removal in a future version. Use timezone-aware objects to represent datetimes in UTC: datetime.datetime.now(datetime.UTC).
  time=datetime.utcnow(),
15:23:10 WARNING opendrift.models.shipdrift:181: Ratio of beam to length should be in range 0.12 to 0.18, given range is 0.25-0.25. Using border value.
15:23:10 INFO    opendrift.models.basemodel.environment:206: Adding a global landmask from GSHHG
15:23:14 INFO    opendrift.models.basemodel.environment:229: Fallback values will be used for the following variables which have no readers:
15:23:14 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_x_velocity: 0.000000
15:23:14 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_y_velocity: 0.000000
15:23:14 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_significant_height: 0.000000
15:23:14 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment: 0.000000

Running model

o.run(steps=24, stop_on_error=True)

15:23:14 INFO    opendrift:907: Using existing reader for land_binary_mask
15:23:14 INFO    opendrift:936: All points are in ocean
15:23:14 INFO    opendrift:2069: 2025-05-09 15:23:10.729027 - step 1 of 24 - 1000 active elements (0 deactivated)
15:23:14 INFO    opendrift.readers:61: Opening file with xr.open_dataset
15:23:16 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'x': 'x', 'y': 'y', 'time': 'time'}
15:23:16 INFO    opendrift.readers:61: Opening file with xr.open_dataset
15:23:17 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'time': 'time', 'x': 'x', 'y': 'y'}
15:23:17 INFO    opendrift.readers:61: Opening file with xr.open_dataset
15:23:21 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'y': 'rlat', 'x': 'rlon', 'time': 'time'}
15:23:23 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:23 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:26 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:23:26 INFO    opendrift:2069: 2025-05-09 16:23:10.729027 - step 2 of 24 - 1000 active elements (0 deactivated)
15:23:27 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:27 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:28 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:23:28 INFO    opendrift:2069: 2025-05-09 17:23:10.729027 - step 3 of 24 - 1000 active elements (0 deactivated)
15:23:30 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:30 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:30 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:23:30 INFO    opendrift:2069: 2025-05-09 18:23:10.729027 - step 4 of 24 - 1000 active elements (0 deactivated)
15:23:32 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:32 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:33 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:23:33 INFO    opendrift:2069: 2025-05-09 19:23:10.729027 - step 5 of 24 - 1000 active elements (0 deactivated)
15:23:35 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:35 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:35 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:23:35 INFO    opendrift:2069: 2025-05-09 20:23:10.729027 - step 6 of 24 - 1000 active elements (0 deactivated)
15:23:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:38 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:23:38 INFO    opendrift:2069: 2025-05-09 21:23:10.729027 - step 7 of 24 - 1000 active elements (0 deactivated)
15:23:40 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:40 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:41 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:23:41 INFO    opendrift:2069: 2025-05-09 22:23:10.729027 - step 8 of 24 - 1000 active elements (0 deactivated)
15:23:42 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:42 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:43 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:23:43 INFO    opendrift:2069: 2025-05-09 23:23:10.729027 - step 9 of 24 - 1000 active elements (0 deactivated)
15:23:45 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:45 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:46 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:23:46 INFO    opendrift:2069: 2025-05-10 00:23:10.729027 - step 10 of 24 - 1000 active elements (0 deactivated)
15:23:48 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:48 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:49 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:23:49 INFO    opendrift:2069: 2025-05-10 01:23:10.729027 - step 11 of 24 - 1000 active elements (0 deactivated)
15:23:50 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:50 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:51 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:23:51 INFO    opendrift:2069: 2025-05-10 02:23:10.729027 - step 12 of 24 - 1000 active elements (0 deactivated)
15:23:53 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:53 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:54 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:23:54 INFO    opendrift:2069: 2025-05-10 03:23:10.729027 - step 13 of 24 - 1000 active elements (0 deactivated)
15:23:56 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:56 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:57 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:23:57 INFO    opendrift:2069: 2025-05-10 04:23:10.729027 - step 14 of 24 - 1000 active elements (0 deactivated)
15:23:59 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:59 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:23:59 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:23:59 INFO    opendrift:2069: 2025-05-10 05:23:10.729027 - step 15 of 24 - 1000 active elements (0 deactivated)
15:24:01 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:01 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:02 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:24:02 INFO    opendrift:2069: 2025-05-10 06:23:10.729027 - step 16 of 24 - 1000 active elements (0 deactivated)
15:24:04 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:04 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:05 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:24:05 INFO    opendrift:2069: 2025-05-10 07:23:10.729027 - step 17 of 24 - 1000 active elements (0 deactivated)
15:24:06 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:06 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:07 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:24:07 INFO    opendrift:2069: 2025-05-10 08:23:10.729027 - step 18 of 24 - 1000 active elements (0 deactivated)
15:24:09 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:09 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:10 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:24:10 INFO    opendrift:2069: 2025-05-10 09:23:10.729027 - step 19 of 24 - 1000 active elements (0 deactivated)
15:24:12 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:12 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:12 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:24:12 INFO    opendrift:2069: 2025-05-10 10:23:10.729027 - step 20 of 24 - 1000 active elements (0 deactivated)
15:24:14 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:14 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:15 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:24:15 INFO    opendrift:2069: 2025-05-10 11:23:10.729027 - step 21 of 24 - 1000 active elements (0 deactivated)
15:24:17 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:17 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:18 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:24:18 INFO    opendrift:2069: 2025-05-10 12:23:10.729027 - step 22 of 24 - 1000 active elements (0 deactivated)
15:24:20 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:20 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:20 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:24:20 INFO    opendrift:2069: 2025-05-10 13:23:10.729027 - step 23 of 24 - 1000 active elements (0 deactivated)
15:24:22 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:22 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:23 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:24:23 INFO    opendrift:2069: 2025-05-10 14:23:10.729027 - step 24 of 24 - 1000 active elements (0 deactivated)
15:24:25 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:25 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:24:26 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction

<xarray.Dataset> Size: 2MB
Dimensions:                                                                              (
                                                                                          trajectory: 1000,
                                                                                          time: 25)
Coordinates:
  * trajectory                                                                           (trajectory) int64 8kB ...
  * time                                                                                 (time) datetime64[ns] 200B ...
Data variables: (12/24)
    status                                                                               (trajectory, time) float32 100kB ...
    moving                                                                               (trajectory, time) float32 100kB ...
    age_seconds                                                                          (trajectory, time) float32 100kB ...
    origin_marker                                                                        (trajectory, time) float32 100kB ...
    lon                                                                                  (trajectory, time) float32 100kB ...
    lat                                                                                  (trajectory, time) float32 100kB ...
    ...                                                                                   ...
    x_sea_water_velocity                                                                 (trajectory, time) float32 100kB ...
    y_sea_water_velocity                                                                 (trajectory, time) float32 100kB ...
    sea_surface_wave_stokes_drift_x_velocity                                             (trajectory, time) float32 100kB ...
    sea_surface_wave_stokes_drift_y_velocity                                             (trajectory, time) float32 100kB ...
    sea_surface_wave_significant_height                                                  (trajectory, time) float32 100kB ...
    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment  (trajectory, time) float32 100kB ...
Attributes: (12/96)
    Conventions:                                                             ...
    standard_name_vocabulary:                                                ...
    featureType:                                                             ...
    title:                                                                   ...
    summary:                                                                 ...
    keywords:                                                                ...
    ...                                                                                                               ...
    geospatial_lon_units:                                                    ...
    geospatial_lon_resolution:                                               ...
    runtime:                                                                 ...
    geospatial_vertical_min:                                                 ...
    geospatial_vertical_max:                                                 ...
    geospatial_vertical_positive:                                            ...

xarray.Dataset

• Dimensions:
  • trajectory: 1000
  • time: 25
• Coordinates: (2)
  • trajectory
    (trajectory)
    int64
    0 1 2 3 4 5 ... 995 996 997 998 999

    cf_role :

    trajectory_id

    dtype :

    <class 'numpy.int32'>

    array([  0,   1,   2, ..., 997, 998, 999], shape=(1000,))

  • time
    (time)
    datetime64[ns]
    2025-05-09T15:23:10.729027 ... 2...

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2025-05-09T15:23:10.729027000', '2025-05-09T16:23:10.729027000',
           '2025-05-09T17:23:10.729027000', '2025-05-09T18:23:10.729027000',
           '2025-05-09T19:23:10.729027000', '2025-05-09T20:23:10.729027000',
           '2025-05-09T21:23:10.729027000', '2025-05-09T22:23:10.729027000',
           '2025-05-09T23:23:10.729027000', '2025-05-10T00:23:10.729027000',
           '2025-05-10T01:23:10.729027000', '2025-05-10T02:23:10.729027000',
           '2025-05-10T03:23:10.729027000', '2025-05-10T04:23:10.729027000',
           '2025-05-10T05:23:10.729027000', '2025-05-10T06:23:10.729027000',
           '2025-05-10T07:23:10.729027000', '2025-05-10T08:23:10.729027000',
           '2025-05-10T09:23:10.729027000', '2025-05-10T10:23:10.729027000',
           '2025-05-10T11:23:10.729027000', '2025-05-10T12:23:10.729027000',
           '2025-05-10T13:23:10.729027000', '2025-05-10T14:23:10.729027000',
           '2025-05-10T15:23:10.729027000'], dtype='datetime64[ns]')

• Data variables: (24)
  • status
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.int32'>

    valid_range :

    [0 0]

    flag_values :

    [0]

    flag_meanings :

    active

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • moving
    (trajectory, time)
    float32
    1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0

    dtype :

    <class 'numpy.int32'>

    minval :

    1

    maxval :

    1

    array([[1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           ...,
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.]], shape=(1000, 25), dtype=float32)

  • age_seconds
    (trajectory, time)
    float32
    0.0 3.6e+03 ... 8.28e+04 8.64e+04

    dtype :

    <class 'numpy.float32'>

    units :

    s

    minval :

    0.0

    maxval :

    86400.0

    array([[    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           ...,
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.]],
          shape=(1000, 25), dtype=float32)

  • origin_marker
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.int32'>

    unit :

    description :

    An integer kept constant during the simulation. Different values may be used for different seedings, to separate elements during analysis. With GUI, only a single seeding is possible.

    flag_values :

    [0]

    flag_meanings :

    Seed_0

    minval :

    0

    maxval :

    0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • lon
    (trajectory, time)
    float32
    5.035 5.036 5.072 ... 5.528 5.551

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    4.938038

    maxval :

    5.855451

    array([[5.0348186, 5.0359106, 5.0724163, ..., 5.428465 , 5.4369354,
            5.433216 ],
           [5.007899 , 5.004911 , 5.061482 , ..., 5.5518155, 5.553606 ,
            5.5155597],
           [5.0193124, 5.0464764, 5.078459 , ..., 5.578812 , 5.580763 ,
            5.5834665],
           ...,
           [5.0018587, 5.026843 , 5.0727277, ..., 5.676998 , 5.7001133,
            5.707893 ],
           [4.9773602, 4.986137 , 5.0205216, ..., 5.425924 , 5.454315 ,
            5.491835 ],
           [4.9929357, 5.021611 , 5.0586786, ..., 5.5327187, 5.527975 ,
            5.5505204]], shape=(1000, 25), dtype=float32)

  • lat
    (trajectory, time)
    float32
    63.0 63.03 63.06 ... 63.28 63.28

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    axis :

    Y

    minval :

    62.973133

    maxval :

    63.614532

    array([[63.004982, 63.034733, 63.05505 , ..., 63.408806, 63.432365,
            63.438038],
           [63.008007, 63.029438, 63.04092 , ..., 63.272972, 63.28122 ,
            63.275383],
           [62.99621 , 63.012398, 63.0176  , ..., 63.269035, 63.28062 ,
            63.2864  ],
           ...,
           [63.001423, 63.018936, 63.032097, ..., 63.296513, 63.283413,
            63.28896 ],
           [62.989754, 63.020813, 63.043026, ..., 63.461742, 63.47169 ,
            63.49448 ],
           [62.98824 , 62.9999  , 63.01972 , ..., 63.26612 , 63.276398,
            63.275326]], shape=(1000, 25), dtype=float32)

  • z
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    standard_name :

    z

    long_name :

    vertical position

    axis :

    Z

    positive :

    up

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • orientation
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 1.0 1.0 1.0 1.0

    dtype :

    <class 'numpy.uint8'>

    units :

    1

    minval :

    0

    maxval :

    1

    array([[0., 0., 0., ..., 0., 0., 0.],
           [1., 1., 1., ..., 1., 1., 1.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [1., 1., 1., ..., 1., 1., 1.],
           [0., 0., 0., ..., 0., 0., 0.],
           [1., 1., 1., ..., 1., 1., 1.]], shape=(1000, 25), dtype=float32)

  • length
    (trajectory, time)
    float32
    80.0 80.0 80.0 ... 80.0 80.0 80.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    500

    description :

    Length of ship

    level :

    1

    minval :

    80.0

    maxval :

    80.0

    array([[80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           ...,
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.]],
          shape=(1000, 25), dtype=float32)

  • height
    (trajectory, time)
    float32
    9.0 9.0 9.0 9.0 ... 9.0 9.0 9.0 9.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    100

    description :

    Total height of ship (above and below waterline)

    level :

    1

    minval :

    9.0

    maxval :

    9.0

    array([[9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           ...,
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.]], shape=(1000, 25), dtype=float32)

  • draft
    (trajectory, time)
    float32
    4.0 4.0 4.0 4.0 ... 4.0 4.0 4.0 4.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    30

    description :

    Draft of ship (depth below water)

    level :

    1

    minval :

    4.0

    maxval :

    4.0

    array([[4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           ...,
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.]], shape=(1000, 25), dtype=float32)

  • beam
    (trajectory, time)
    float32
    20.0 20.0 20.0 ... 20.0 20.0 20.0

    dtype :

    <class 'numpy.float32'>

    min :

    1

    max :

    70

    units :

    m

    description :

    Beam (width) of ship

    level :

    1

    minval :

    20.0

    maxval :

    20.0

    array([[20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           ...,
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.]],
          shape=(1000, 25), dtype=float32)

  • wind_drag_coeff
    (trajectory, time)
    float32
    0.815 0.815 0.815 ... 0.815 0.815

    dtype :

    <class 'numpy.float32'>

    units :

    1

    minval :

    0.815

    maxval :

    0.815

    array([[0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           ...,
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815]],
          shape=(1000, 25), dtype=float32)

  • water_drag_coeff
    (trajectory, time)
    float32
    1.32 1.32 1.32 ... 1.32 1.32 1.32

    dtype :

    <class 'numpy.float32'>

    units :

    1

    minval :

    1.32

    maxval :

    1.32

    array([[1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           ...,
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32]],
          shape=(1000, 25), dtype=float32)

  • jibeProbability
    (trajectory, time)
    float32
    0.04 0.04 0.04 ... 0.04 0.04 0.04

    dtype :

    <class 'numpy.float32'>

    units :

    1/h

    minval :

    0.04

    maxval :

    0.04

    array([[0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           ...,
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04]],
          shape=(1000, 25), dtype=float32)

  • x_wind
    (trajectory, time)
    float32
    4.083 3.806 3.474 ... 0.2386 0.2386

    minval :

    -1.3974177

    maxval :

    6.84809

    array([[ 4.0829487 ,  3.8059921 ,  3.4742417 , ...,  2.0277998 ,
             0.3381706 ,  0.3381706 ],
           [ 2.5755599 ,  2.323927  ,  3.4728727 , ...,  1.9853643 ,
            -0.02014653, -0.02014653],
           [ 3.98731   ,  4.3661656 ,  4.1247606 , ..., -0.09630442,
            -1.230125  , -1.230125  ],
           ...,
           [ 3.9968545 ,  4.956321  ,  5.330765  , ..., -0.3213212 ,
            -0.53848046, -0.53848046],
           [ 5.249933  ,  5.9660773 ,  5.300611  , ...,  2.959127  ,
             2.4782102 ,  2.4782102 ],
           [ 5.0877542 ,  4.877324  ,  4.483177  , ...,  2.2551386 ,
             0.23863906,  0.23863906]], shape=(1000, 25), dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    6.983 6.803 6.827 ... 4.893 4.893

    minval :

    3.38473

    maxval :

    11.209317

    array([[6.983147 , 6.8027773, 6.8272233, ..., 4.624035 , 4.811899 ,
            4.811899 ],
           [5.8585386, 5.4375296, 6.007178 , ..., 3.8498466, 3.7440457,
            3.7440457],
           [5.6037807, 5.974197 , 6.153786 , ..., 3.7319195, 3.6943796,
            3.6943796],
           ...,
           [6.1698375, 6.2662735, 6.330357 , ..., 4.4647284, 4.7000685,
            4.7000685],
           [6.460327 , 6.6876354, 6.7597365, ..., 6.2894354, 5.8231835,
            5.8231835],
           [6.2325225, 6.3510756, 6.315494 , ..., 4.6838984, 4.8930044,
            4.8930044]], shape=(1000, 25), dtype=float32)

  • land_binary_mask
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • x_sea_water_velocity
    (trajectory, time)
    float32
    0.2452 0.2447 ... 0.1066 0.1066

    minval :

    -0.094303705

    maxval :

    0.34785667

    array([[0.24522209, 0.24470314, 0.23766352, ..., 0.05504282, 0.06461176,
            0.06461176],
           [0.24478972, 0.24428631, 0.24235785, ..., 0.0557274 , 0.10200516,
            0.10200516],
           [0.24301304, 0.24623862, 0.2405051 , ..., 0.04667535, 0.09727947,
            0.09727947],
           ...,
           [0.24502052, 0.24634995, 0.24204597, ..., 0.03666737, 0.09120316,
            0.09120316],
           [0.2452305 , 0.24421562, 0.24179944, ..., 0.04707878, 0.05143048,
            0.05143048],
           [0.24269274, 0.24675974, 0.24328911, ..., 0.06584702, 0.10663047,
            0.10663047]], shape=(1000, 25), dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    0.3117 0.3233 ... 0.1076 0.1076

    minval :

    -0.11761169

    maxval :

    0.47239712

    array([[0.3116576 , 0.32328805, 0.3105181 , ..., 0.29164124, 0.325507  ,
            0.325507  ],
           [0.34470427, 0.3549716 , 0.32065192, ..., 0.1131646 , 0.09166637,
            0.09166637],
           [0.3316483 , 0.3141455 , 0.2908472 , ..., 0.10154555, 0.0793058 ,
            0.0793058 ],
           ...,
           [0.35573363, 0.3368076 , 0.3008941 , ..., 0.09124944, 0.08078046,
            0.08078046],
           [0.3703203 , 0.3653728 , 0.3627226 , ..., 0.34708655, 0.35602188,
            0.35602188],
           [0.35719377, 0.3464562 , 0.32021293, ..., 0.12433504, 0.10758393,
            0.10758393]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_stokes_drift_x_velocity
    (trajectory, time)
    float32
    0.06699 0.06823 ... 0.05882 0.05882

    minval :

    0.056012865

    maxval :

    0.08979046

    array([[0.06698538, 0.06823416, 0.07038462, ..., 0.06184206, 0.05965152,
            0.05965152],
           [0.06637296, 0.0668432 , 0.06986323, ..., 0.06275865, 0.05896549,
            0.05896549],
           [0.06673197, 0.06922718, 0.070916  , ..., 0.06261296, 0.05895051,
            0.05895051],
           ...,
           [0.0661606 , 0.06844453, 0.07001397, ..., 0.06094449, 0.05814031,
            0.05814031],
           [0.06427781, 0.06605662, 0.0683547 , ..., 0.06248965, 0.05880013,
            0.05880013],
           [0.06521749, 0.0688749 , 0.07037444, ..., 0.06253085, 0.0588209 ,
            0.0588209 ]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_stokes_drift_y_velocity
    (trajectory, time)
    float32
    0.06992 0.07509 ... 0.04582 0.04582

    minval :

    0.033630323

    maxval :

    0.12969725

    array([[0.06991506, 0.07508638, 0.07487485, ..., 0.06318957, 0.05802647,
            0.05802647],
           [0.07175421, 0.07635406, 0.07578891, ..., 0.05140611, 0.04501884,
            0.04501884],
           [0.07007585, 0.07371822, 0.07453876, ..., 0.05102725, 0.04442104,
            0.04442104],
           ...,
           [0.07156215, 0.07509112, 0.07582834, ..., 0.04798693, 0.04081912,
            0.04081912],
           [0.07116208, 0.07692994, 0.07732957, ..., 0.06821747, 0.0596742 ,
            0.0596742 ],
           [0.07038204, 0.07444362, 0.07530449, ..., 0.05244359, 0.04582132,
            0.04582132]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_significant_height
    (trajectory, time)
    float32
    1.351 1.404 1.425 ... 2.136 2.136

    minval :

    1.3265523

    maxval :

    2.3520982

    array([[1.3513906, 1.4042606, 1.4251976, ..., 2.140973 , 2.2044914,
            2.2044914],
           [1.3589013, 1.4081404, 1.4263408, ..., 2.0881457, 2.1364346,
            2.1364346],
           [1.3474815, 1.3883204, 1.4128559, ..., 2.0899704, 2.1373067,
            2.1373067],
           ...,
           [1.3544886, 1.3966882, 1.4225681, ..., 2.072755 , 2.1091194,
            2.1091194],
           [1.3454866, 1.403874 , 1.438731 , ..., 2.147374 , 2.192985 ,
            2.192985 ],
           [1.34264  , 1.3835505, 1.4184761, ..., 2.0862052, 2.1358244,
            2.1358244]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment
    (trajectory, time)
    float32
    4.469 4.484 4.497 ... 6.558 6.558

    minval :

    4.3452234

    maxval :

    6.59947

    array([[4.4688888, 4.4837055, 4.4969215, ..., 6.207975 , 6.4839334,
            6.4839334],
           [4.469788 , 4.480499 , 4.4886093, ..., 6.247778 , 6.556821 ,
            6.556821 ],
           [4.4603863, 4.460605 , 4.467026 , ..., 6.251669 , 6.5588875,
            6.5588875],
           ...,
           [4.463681 , 4.466895 , 4.4784107, ..., 6.2720547, 6.570155 ,
            6.570155 ],
           [4.455362 , 4.4658613, 4.5011997, ..., 6.144905 , 6.4526844,
            6.4526844],
           [4.4543033, 4.444768 , 4.4735975, ..., 6.2468014, 6.5582056,
            6.5582056]], shape=(1000, 25), dtype=float32)

• Indexes: (2)
  • trajectory
    PandasIndex

    PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,
           ...
           990, 991, 992, 993, 994, 995, 996, 997, 998, 999],
          dtype='int64', name='trajectory', length=1000))

  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2025-05-09 15:23:10.729027', '2025-05-09 16:23:10.729027',
                   '2025-05-09 17:23:10.729027', '2025-05-09 18:23:10.729027',
                   '2025-05-09 19:23:10.729027', '2025-05-09 20:23:10.729027',
                   '2025-05-09 21:23:10.729027', '2025-05-09 22:23:10.729027',
                   '2025-05-09 23:23:10.729027', '2025-05-10 00:23:10.729027',
                   '2025-05-10 01:23:10.729027', '2025-05-10 02:23:10.729027',
                   '2025-05-10 03:23:10.729027', '2025-05-10 04:23:10.729027',
                   '2025-05-10 05:23:10.729027', '2025-05-10 06:23:10.729027',
                   '2025-05-10 07:23:10.729027', '2025-05-10 08:23:10.729027',
                   '2025-05-10 09:23:10.729027', '2025-05-10 10:23:10.729027',
                   '2025-05-10 11:23:10.729027', '2025-05-10 12:23:10.729027',
                   '2025-05-10 13:23:10.729027', '2025-05-10 14:23:10.729027',
                   '2025-05-10 15:23:10.729027'],
                  dtype='datetime64[ns]', name='time', freq='h'))

• Attributes: (96)

  Conventions :

  CF-1.11, ACDD-1.3

  standard_name_vocabulary :

  CF Standard Name Table v85

  featureType :

  trajectory

  title :

  OpenDrift trajectory simulation

  summary :

  Output from simulation with OpenDrift framework

  keywords :

  trajectory, drift, lagrangian, simulation

  history :

  Created 2025-05-09 15:23:14.827733

  date_created :

  2025-05-09T15:23:14.827741

  source :

  Output from simulation with OpenDrift

  model_url :

  https://github.com/OpenDrift/opendrift

  opendrift_class :

  ShipDrift

  opendrift_module :

  opendrift.models.shipdrift

  readers :

  odict_keys(['LazyReader: https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'LazyReader: https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc', 'LazyReader: https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml', 'global_landmask'])

  time_coverage_start :

  2025-05-09 15:23:10.729027

  time_step_calculation :

  1:00:00

  time_step_output :

  1:00:00

  config_environment:constant:x_wind :

  None

  config_environment:fallback:x_wind :

  None

  config_environment:constant:y_wind :

  None

  config_environment:fallback:y_wind :

  None

  config_environment:constant:land_binary_mask :

  None

  config_environment:fallback:land_binary_mask :

  None

  config_environment:constant:x_sea_water_velocity :

  None

  config_environment:fallback:x_sea_water_velocity :

  None

  config_environment:constant:y_sea_water_velocity :

  None

  config_environment:fallback:y_sea_water_velocity :

  None

  config_environment:constant:sea_surface_wave_stokes_drift_x_velocity :

  None

  config_environment:fallback:sea_surface_wave_stokes_drift_x_velocity :

  0

  config_environment:constant:sea_surface_wave_stokes_drift_y_velocity :

  None

  config_environment:fallback:sea_surface_wave_stokes_drift_y_velocity :

  0

  config_environment:constant:sea_surface_wave_significant_height :

  None

  config_environment:fallback:sea_surface_wave_significant_height :

  0

  config_environment:constant:sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  None

  config_environment:fallback:sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  0

  config_general:use_auto_landmask :

  True

  config_drift:current_uncertainty :

  0

  config_drift:current_uncertainty_uniform :

  0

  config_drift:max_speed :

  2.0

  config_readers:max_number_of_fails :

  1

  config_general:simulation_name :

  config_general:coastline_action :

  stranding

  config_general:coastline_approximation_precision :

  0.001

  config_general:time_step_minutes :

  60

  config_general:time_step_output_minutes :

  None

  config_seed:ocean_only :

  True

  config_seed:number :

  1

  config_drift:max_age_seconds :

  None

  config_drift:advection_scheme :

  euler

  config_drift:horizontal_diffusivity :

  100.0

  config_drift:profiles_depth :

  50

  config_drift:wind_uncertainty :

  0

  config_drift:relative_wind :

  False

  config_drift:deactivate_north_of :

  None

  config_drift:deactivate_south_of :

  None

  config_drift:deactivate_east_of :

  None

  config_drift:deactivate_west_of :

  None

  config_seed:origin_marker :

  0

  config_seed:z :

  0

  config_seed:orientation :

  random

  config_seed:length :

  80

  config_seed:height :

  8

  config_seed:draft :

  4.0

  config_seed:beam :

  10

  config_seed:wind_drag_coeff :

  1

  config_seed:water_drag_coeff :

  1

  config_seed:jibeProbability :

  0.04

  opendrift_version :

  1.13.1

  seed_geojson :

  {"features": [], "type": "FeatureCollection"}

  simulation_time :

  2025-05-09 15:23:14.897167

  reader_x_wind :

  ['https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc']

  reader_y_wind :

  ['https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc']

  reader_land_binary_mask :

  ['global_landmask']

  reader_x_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_y_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_stokes_drift_x_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_stokes_drift_y_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_significant_height :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  time_coverage_end :

  2025-05-10 15:23:10.729027

  time_coverage_duration :

  P1DT0H0M0S

  time_coverage_resolution :

  P0DT1H0M0S

  performance :

  -------------------- Reader performance: -------------------- global_landmask 0:00:00.0 total 0:00:00.0 preparing 0:00:00.0 reading 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml 0:00:14.4 total 0:00:00.0 preparing 0:00:14.4 reading 0:00:00.0 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc 0:00:30.8 total 0:00:00.0 preparing 0:00:30.8 reading 0:00:00.2 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml 0:00:18.8 total 0:00:00.0 preparing 0:00:18.8 reading 0:00:00.0 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- Performance: 1:15.7 total time 4.1 configuration 0.0 preparing main loop 0.0 moving elements to ocean 1:11.5 main loop 0.4 updating elements 0.0 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  62.973133

  geospatial_lat_max :

  63.614532

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  4.938038

  geospatial_lon_max :

  5.855451

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:01:15.749649

  geospatial_vertical_min :

  0.0

  geospatial_vertical_max :

  0.0

  geospatial_vertical_positive :

  up

Print and plot results

print(o)
o.plot(linecolor='orientation')
#o.animation(color='orientation', markersize=20, filename="orientation.gif", legend=['left','right'],colorbar=False,cmap='bwr')
o.animation(color='orientation', legend=['left','right'], markersize=20, colorbar=False, cmap='bwr')

===========================
--------------------
Reader performance:
--------------------
global_landmask
 0:00:00.0  total
 0:00:00.0  preparing
 0:00:00.0  reading
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
 0:00:14.4  total
 0:00:00.0  preparing
 0:00:14.4  reading
 0:00:00.0  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc
 0:00:30.8  total
 0:00:00.0  preparing
 0:00:30.8  reading
 0:00:00.2  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml
 0:00:18.8  total
 0:00:00.0  preparing
 0:00:18.8  reading
 0:00:00.0  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
Performance:
 1:15.7 total time
    4.1 configuration
    0.0 preparing main loop
      0.0 moving elements to ocean
 1:11.5 main loop
      0.4 updating elements
    0.0 cleaning up
--------------------
===========================
Model:  ShipDrift     (OpenDrift version 1.13.1)
        1000 active ShipObject particles  (0 deactivated, 0 scheduled)
-------------------
Environment variables:
  -----
  land_binary_mask
     1) global_landmask
  -----
  x_sea_water_velocity
  y_sea_water_velocity
     1) https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
     2) https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml
  -----
  x_wind
  y_wind
     1) https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc
  -----
  sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment
  sea_surface_wave_significant_height
  sea_surface_wave_stokes_drift_x_velocity
  sea_surface_wave_stokes_drift_y_velocity
     1) https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml

Discarded readers:

Time:
        Start: 2025-05-09 15:23:10.729027 UTC
        Present: 2025-05-10 15:23:10.729027 UTC
        Calculation steps: 24 * 1:00:00 - total time: 1 day, 0:00:00
        Output steps: 25 * 1:00:00
===========================

15:25:05 INFO    opendrift:4617: Saving animation to /root/project/docs/source/gallery/animations/example_shipdrift_0.gif...
15:25:27 INFO    opendrift:3053: Time to make animation: 0:00:22.707582